Genetic analysis of yield and fiber quality traits in cotton (Gossypium hirsutum L.) under full and deficit irrigation conditions using full diallel method

Author:

Gören Hatice Kübra,Canavar Öner

Abstract

AbstractThe aim of the study was to assess the genetic structure and quantitative heritability of cotton yield, yield components and fiber quality parameters under well-watered (100%) and deficit (50%) irrigation conditions using a complete full diallel cross method with six cotton genotypes. The F1 and F2 generations were obtained to study the effect of irrigation conditions on genotypic variation and maternal effects on the traits studied. Parental, F1 and F2 generations were growed under full and deficit irrigation conditions and selected agronomic and fiber quality traits were measured. The data were analysed using various methods, including Griffing Method I, Model I analysis of variance, full diallel table analysis of variance, Jinks-Hayman diallel hybrid analysis. The Jinks-Hayman analysis of variance showed that dominant effects were more important in the inheritance of all traits, as indicated by the negative value of the difference between the additive variance and the dominance variance (D-H1). In addition, the average degree of dominance (H1/D)1/2 was greater than 1, indicating the predominance of dominant gene action in inheritance. The study concluded that starting selection in the F5–F6 generation is appropriate for drought resistant cotton breeding studies. It also emphasised the importance of conducting drought resistant cotton breeding under drought conditions due to the differences in gene movement between well-watered irrigation and drought stress conditions. The study highlighted the importance of population selection, environmental factors, data collection and analysis interpretation in breeding studies. It suggested that the Griffing diallel analysis method is suitable for hybrid breeding studies, while the Jinks-Hayman type analysis method is suitable for studying the genetic structures of populations.

Funder

Unit of Scientifc Research Project, Aydın Adnan Menderes University

Aydin Adnan Menderes University

Publisher

Springer Science and Business Media LLC

Reference106 articles.

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